Survey of interfaces and visualizations of complex networks

Code Red Visualisations

Code Red was a computer worm observed on the internet in July 2001. On the 12th of the month the malware program began to replicated itself to spread to other computers through networks of Microsoft’s IIS web-server. Once a system got attacked the worm checked the system clock of the machine, if the date was between the 1st and the 19th of the month code red generated a random list of IP addresses from a static seed and infected the machines of those IP addresses. From the 20th to the 28th of the month the worm started a Denial-of-Service attack against the website whitehouse.gov. Through a research project at the Interaction Design Laboratories at the University of Applied Sciences Potsdam we tried to find different visualization formats to develop a better understanding of the worm.

Autonomous System Network

Visualisation of 15.000 attacked Autonomous Systems and their connections to each other during the Code Red epidemic. The connectivity of the links is represented by their colour and size. Magenta nodes are only rawly connected. Blue nodes are highly connected autonomous systems also called “hubs”. The connectedness of a node is measured in degrees, how many links do refer and go out from each node. The most attacked node is a not too well connected system within the network, an AS from the Korean Telecom which received 13.835 attacks. It is coloured green within the network. The two most connected nodes are UUNET which was one of the largest Internet providers in the United States it got attacked 10.767 times. And the most connected link toplink GmbH a german VoIP provider which only got attacked 34 times. In many network systems like cells or diseases epidemics spread through the hubs of a system and by doing so also affect those the most. In the chase of code red this can’t be said.

Attacks Radial

All attacks mapped by time and their location in latitude and longitude on a radial layout. Each point represents one attack and the time when it got attacked. The nodes are coloured in by the length of the attack, from red if the system was only attacked for seconds up to 30 hours in blue. All countries with more than 4.000 attacks are mapped around the radial layout by their longitude.

Attacks Timeline

All attacks mapped by time and Autonomous system. The same dataset as the Attacks-Radial-Lat-Lon-Time this time not radial but on a coordinate system. What’s interesting here are the different interpretations we can make from the two datasets. While it becomes clear were the attacks go in the radial version, in this version the anomalies at 17h become much more clearer as well as the abrupt end of the worm after 24h.

Autonomous System Hiveplot

Actually this graphic is not really readable and there are other forms to visualize Autonomous Systems Networks that are more helpful. But in two instances the structuring of the nodes can help to develop an understanding of the network. First it shows how much bigger the two biggest nodes are in the network compared to the rest and it shows the long tail there are a large amount of nodes with only one connection and very little nodes with more than that. This kind of network is very easy to attack and epidemics can spread very quickly.